Abstract

Establishing correspondences between salient
points on 3D shapes results in functions mapping
similar parts of 3D objects. In this paper, we
present a new method for establishing binary
correspondences between salient points on 3D
shapes. Our algorithm is independent of the shape
representation and the object topology and does
not require any prepositioning of the objects. Our
method first detects stable salient points that are
representative for certain parts of the shape. For
each of these salient points it then computes an
associated local shape descriptor. We introduce
a matching energy between the salient points of
two shapes which depends on the similarity of
the descriptors and the spatial relationship of the
salient points. An iterative optimization scheme
determines a correspondence mapping between
the salient points which minimizes this energy.
The resulting binary correspondences between the
salient points can be used for applications like
3D shape retrieval based on similarity estimation,
classification of 3D objects, editing, and statistical
shape analysis. It is especially useful as an initialization
method for approaches relying on prior
knowledge about corresponding points like cross
parameterization or morphing.

Bilder

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Bibtex

@INPROCEEDINGS{wessel-2006-correspondences,
author = {Wessel, Raoul and Novotni, Marcin and Klein, Reinhard},
editor = {Kobbelt, L. and Kuhlen, T. and Aach, T. and Westermann, R.},
pages = {365--372},
title = {Correspondences between Salient Points on 3D Shapes},
booktitle = {Vision, Modeling, and Visualization 2006 (VMV 2006)},
year = {2006},
month = nov,
publisher = {Akademische Verlagsgesellschaft Aka GmbH, Berlin},
abstract = {Establishing correspondences between salient
points on 3D shapes results in functions mapping
similar parts of 3D objects. In this paper, we
present a new method for establishing binary
correspondences between salient points on 3D
shapes. Our algorithm is independent of the shape
representation and the object topology and does
not require any prepositioning of the objects. Our
method first detects stable salient points that are
representative for certain parts of the shape. For
each of these salient points it then computes an
associated local shape descriptor. We introduce
a matching energy between the salient points of
two shapes which depends on the similarity of
the descriptors and the spatial relationship of the
salient points. An iterative optimization scheme
determines a correspondence mapping between
the salient points which minimizes this energy.
The resulting binary correspondences between the
salient points can be used for applications like
3D shape retrieval based on similarity estimation,
classification of 3D objects, editing, and statistical
shape analysis. It is especially useful as an initialization
method for approaches relying on prior
knowledge about corresponding points like cross
parameterization or morphing.},
isbn = {3-89838-081-5},
conference = {Vision, Modeling, and Visualization 2006 (VMV 2006)}
}